Genetics, Epigenetics and Gene Expression Markers of Major Depressive Disorder and Antidepressant Response

The World Journal of Biological Psychiatry

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Consensus paper of the WFSBP Task Force on Genetics: Genetics, epigenetics and gene expression markers of major depressive disorder and antidepressant response

Chiara Fabbri, Ladislav Hosak, Rainald Mössner, Ina Giegling, Laura Mandelli, Frank Bellivier, Stephan Claes, David A. Collier, Alejo Corrales, Lynn E. Delisi, Carla Gallo, Michael Gill, James L. Kennedy, Marion Leboyer, Amanda Lisoway, Wolfgang Maier, Miguel Marquez, Isabelle Massat, Ole Mors, Pierandrea Muglia, Markus M. Nöthen, Michael C. O’Donovan, Jorge Ospina-Duque, Peter Propping, Yongyong Shi, David St Clair, Florence Thibaut, Sven Cichon, Julien Mendlewicz, Dan Rujescu & Alessandro Serretti

To cite this article: Chiara Fabbri, Ladislav Hosak, Rainald Mössner, Ina Giegling, Laura Mandelli, Frank Bellivier, Stephan Claes, David A. Collier, Alejo Corrales, Lynn E. Delisi, Carla Gallo, Michael Gill, James L. Kennedy, Marion Leboyer, Amanda Lisoway, Wolfgang Maier, Miguel Marquez, Isabelle Massat, Ole Mors, Pierandrea Muglia, Markus M. Nöthen, Michael C. O’Donovan, Jorge Ospina-Duque, Peter Propping, Yongyong Shi, David St Clair, Florence Thibaut, Sven Cichon, Julien Mendlewicz, Dan Rujescu & Alessandro Serretti (2017) Consensus paper of the WFSBP Task Force on Genetics: Genetics, epigenetics and gene expression markers of major depressive disorder and antidepressant response, The World Journal of Biological Psychiatry, 18:1, 5-28, DOI: 10.1080/15622975.2016.1208843

To link to this article: http://dx.doi.org/10.1080/15622975.2016.1208843

Published online: 07 Sep 2016.

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Download by: [the Medical University of Vienna], [Professor Siegfried Kasper] Date: 24 January 2017, At: 02:35 THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY, 2017 VOL. 18, NO. 1, 5–28 http://dx.doi.org/10.1080/15622975.2016.1208843

WFSBP CONSENSUS PAPER Consensus paper of the WFSBP Task Force on Genetics: Genetics, epigenetics and gene expression markers of major depressive disorder and antidepressant response

Chiara Fabbria,LadislavHosakb, Rainald Mossner€ c, Ina Gieglingd, Laura Mandellia, Frank Belliviere, Stephan Claesf, David A. Collierg, Alejo Corralesh,LynnE.Delisii,CarlaGalloj, Michael Gillk, James L. Kennedyl, Marion Leboyerm, Amanda Lisowayl, Wolfgang Maiern,MiguelMarquezo, Isabelle Massatp, Ole Morsq, Pierandrea Mugliar,MarkusM.Nothen€ s, Michael C. O’Donovant, Jorge Ospina-Duqueu,PeterProppingv, Yongyong Shiw, David St Clairx, Florence Thibauty , Sven Cichonz, Julien MendlewiczA, Dan Rujescud and Alessandro Serrettia aDepartment of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy; bDepartment of Psychiatrics, Charles University, Faculty of Medicine and University Hospital, Hradec Kralove, Czech Republic; cDepartment of Psychiatry and Psychotherapy, University of Tubingen,€ Tubingen,€ Germany; dDepartment of Psychiatry, Psychotherapy and Psychosomatics, Martin Luther University of Halle-Wittenberg, Halle, Germany; eFondation Fondamental, Creteil, France AP-HP, GH Saint-Louis-Lariboisie`re-Fernand-Widal, P^ole Neurosciences, Paris, France; fGRASP-Research Group, Department of Neuroscience, University of Leuven, Leuven, Belgium; gSocial, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, London, UK; hNational University (UNT) Argentina, Argentinean Association of Biological Psychiatry, Buenos Aires, Argentina; iVA Boston Health Care System, Brockton, MA, USA; jDepartamento de Ciencias Celulares y Moleculares, Laboratorios de Investigacion y Desarrollo, Facultad de Ciencias y Filosofıa, Universidad Peruana Cayetano Heredia, Lima, Peru; kNeuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Dublin, Ireland; lNeurogenetics Section, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; mFacultede Medecine, Universite Paris-Est Creteil, Inserm U955, Equipe Psychiatrie Translationnelle, Creteil, France; nDepartment of Psychiatry, University of Bonn, Bonn, Germany; oDirector of ADINEU (Asistencia, Docencia e Investigacion en Neurociencia), Buenos Aires, Argentina; pUNI - ULB Neurosciences Institute, ULB, Bruxelles, Belgium; qDepartment P, Aarhus University Hospital, Risskov, Denmark; rUCB Biopharma, Belgium; sInstitute of Human Genetics, University of Bonn, Bonn, Germany; tMRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK; u Grupo de Investigacion en Psiquiatrıa, Departamento de Psiquiatrıa, Facultad de Medicina, Universidad de Antioquia, Medellın, Colombia; vUniversity of Bonn, Germany; wBio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China; xUniversity of Aberdeen, Institute of Medical Sciences, Aberdeen, UK; yUniversity Hospital Cochin (Site Tarnier), University Sorbonne Paris Cite (Faculty of Medicine Paris Descartes), INSERM U 894 Centre Psychiatry and Neurosciences, Paris, France; zDivision of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland; ALaboratoire de Psychologie Medicale, Centre Europeen de Psychologie Medicale, Universite Libre de Bruxelles and Psy Pluriel, Brussels, Belgium

ABSTRACT ARTICLE HISTORY Major depressive disorder (MDD) is a heritable disease with a heavy personal and socio-economic Received 23 June 2016 burden. Antidepressants of different classes are prescribed to treat MDD, but reliable and repro- Accepted 29 June 2016 ducible markers of efficacy are not available for clinical use. Further complicating treatment, the diagnosis of MDD is not guided by objective criteria, resulting in the risk of under- or overtreat- KEYWORDS ment. A number of markers of MDD and antidepressant response have been investigated at the Major depression; genetic, epigenetic, gene expression and protein levels. Polymorphisms in genes involved in anti- antidepressant; genetics- depressant metabolism (cytochrome P450 isoenzymes), antidepressant transport (ABCB1), gluco- epigenetics; transcriptomics- corticoid signalling (FKBP5) and serotonin neurotransmission (SLC6A4 and HTR2A) were among proteomics those included in the first pharmacogenetic assays that have been tested for clinical applicability. The results of these investigations were encouraging when examining patient-outcome improvement. Furthermore, a nine-serum biomarker panel (including BDNF, cortisol and soluble TNF-a receptor type II) showed good sensitivity and specificity in differentiating between MDD and healthy controls. These first diagnostic and response-predictive tests for MDD provided a source of optimism for future clinical applications. However, such findings should be considered very carefully because their benefit/cost ratio and clinical indications were not clearly demonstrated. Future tests may include combinations of different types of biomarkers and be specific for MDD subtypes or pathological dimensions.

CONTACT Dan Rujescu, MD, PhD [email protected] Department of Psychiatry, Psychotherapy and Psychosomatics, Martin-Luther-University Halle-Wittenberg, Julius-Kuhn-Strasse€ 7, Halle 06112, Germany ß 2016 Informa UK Limited, trading as Taylor & Francis Group 6 C. FABBRI ET AL.

1. Introduction strongest risk factors for the development of several psychiatric disorders, including MDD. Gene expression Major depressive disorder (MDD) was among the five (mRNA levels) and protein level measures are useful leading diseases contributing to DALYs in 2010 in the complementary data to genetic and epigenetic infor- USA, after cardiovascular diseases and lung cancer mation, since several levels of regulation occur after (Murray et al. 2013). The disorder also carries with it a gene translation (i.e., post-translational modifications substantial increase in suicide risk (Bradvik et al. 2008), involving addition of functional groups or other pro- a quality of life comparable to that of severe physical teins/peptides, structural changes, catabolic processes). disorders such as arthritis and heart disease (Buist- Blood cells represent an easily available sample for Bouwman et al. 2006) and significant health expendi- gene expression studies and they share between 35 tures, with direct costs alone amounting to 42 billion and 80% of the transcriptome with the brain (Tylee dollars in Europe (Sobocki et al. 2006). et al. 2013). A particular type of ribonucleic acid (RNA) Despite the demonstrated efficacy of antidepressant known as microRNA (miRNA) received attention medications, high inter-individual variability is observed recently because miRNAs function as modulators of in both response and side-effect occurrence and the the degradation and translation of messenger RNA lack of reliable markers of these outcomes contributes (mRNA), thus they represent a fundamental regulatory to unsatisfactory treatment effectiveness, poor treat- step in the process leading to protein production. ment adherence and early treatment discontinuation Proteins can be dosed in serum or plasma and differ- (Fabbri et al. 2013a). Furthermore, few studies include ent protocols can be applied, thereby showing the or adjust for placebo response, which has been shown results of proteomic studies are affected by preanalyti- to account for 67.6% of the efficacy observed in anti- cal and analytical variability often resulting in poor depressant treatment (Rief et al. 2009). Placebo comparability among different studies. Furthermore, response is a major concern for drug trials, as well as new methods for quantitative proteomics were for biomarker investigations, and likely has a significant recently developed to increase the precision, robust- genetic component (Walsh et al. 2002; Tiwari et al. ness, and resolution of protein measurement (Li et al. 2013; Holmes et al. 2016). Importantly, objective criteria 2015). are not available to support the diagnosis of MDD We emphasise that markers of acute depressive based on clinical criteria only, resulting in the risk of phases (i.e., state markers such as the expression level clinician-dependent variability in terms of both diagno- of inflammatory genes) are distinct from markers of sus- sis type and severity. Indeed, two well-known scenarios ceptibility to MDD (i.e., markers of vulnerability to the are observed in clinical settings: the diagnosis conflates disease such as genetic variants), but they partially over- adaptive sadness reactions with pathological states of lap and are not always easy to distinguish. For example depressed mood, resulting in overdiagnosis and over- the expression level of some genes may be altered treatment; on the other hand, underdiagnosis and especially during the acute phases, but it may not com- undertreatment may lead to a severe, chronic, recur- pletely normalise after symptom remission. The avail- rent or treatment-resistant course (Lorenzo-Luaces able evidence for gene expression levels was mostly 2015). obtained during the acute phase of MDD. Finally, the Research has been oriented toward the identifica- aetiopathogenesis of MDD is hypothesised to partially tion of biomarkers of MDD and antidepressant treat- but not completely overlap with the mechanisms of ment outcomes, i.e., genetic or epigenetic variations, antidepressant drug action, thus the sections discussing measures of gene expression or protein levels. Genetic the markers of antidepressant efficacy have been sepa- variations that have been investigated in this field are rated from those discussing the markers of MDD. mainly common single-nucleotide polymorphisms (SNPs). Common SNPs alone have been estimated to 2. Methods explain about 42% of the variance in antidepressant response (Tansey et al. 2013). Epigenetics refers to the The present review is focused on biomarkers of MDD study of phenotypic variations that are not caused by and antidepressant responses that may be nearest to DNA sequence modifications and it includes gene clinical applications, i.e., biomarkers that: methylation and histone modifications. Epigenetic profiles are inherited but are responsive to environmental 1. have an association with the phenotypes of inter- stress, especially during early development (Jaenisch est at several ‘‘omics’’ levels (genetic, epigenetic and Bird, 2003). Indeed, exposure to stressful or trau- and/or peripheral blood transcriptomics/ matic life events, especially early in life, is one of the proteomics); THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 7

2. are supported by at least one meta-analysis or 3.1.1. Genetic polymorphisms replicated results in the same direction by at least Known polymorphisms in the gene coding for the three studies in conjunction with consistent data SERT (SLC6A4) produce alterations in the expression from translational studies. level and are hypothesised to affect both the risk of affective disorders and antidepressant response. In In addition to these criteria, biomarkers that have detail, the short (S) allele (14-repeats) of the 5-HTTLPR been included in a pilot study testing clinical applic- insertion/deletion polymorphism determines a half ability (in terms of individual and possibly economic basal expression of SERT compared to the long (L) benefits) are also included in this review. allele (16-repeats) (Heils et al. 1996), as well as when For an overview of markers in the first and second compared to the L allele combination with the G allele group see Tables 1 and 2, respectively. Finally, a section is dedicated to new promising bio- of the rs25531 polymorphism (LG) (Hu et al. 2006). A markers, including miRNAs and, for example, methodo- number of genetic studies investigated the effect of logical approaches such as polygenic risk scores (PRS). the 5-HTTLPR polymorphism on susceptibility to MDD, The data used for this review have been extracted and two meta-analyses reported absent or negligible from MEDLINE, EMBASE and Web of Science (ISI) and effects (Munafo et al. 2009; Risch et al. 2009). However, include articles published up to February 2016. these meta-analyses included only a minority of the available studies. A more recent and comprehensive study found strong evidence that 5-HTTLPR moderates 3. Serotonergic neurotransmission the relationship between stress and depression, with Serotonin (5-HT) is known to be involved in many an association between the S allele and the risk of physiological and behavioural processes that are dysre- developing depression under stress (Karg et al. 2011). gulated in MDD, including mood, appetite, sleep, activ- Stratification of the analysis for the type of stressor ity, suicide, sexual behaviour and cognition. The showed a stronger risk effect of the S allele in cases of decreased levels of 5-HT metabolites in cerebrospinal childhood maltreatment and medical conditions. A fluid (CSF), coupled with the mood-lowering effects of more recent study on a cohort of 5,249 individuals assessed at birth and followed up to the age of 18 tryptophan depletion and the efficacy of serotonin- modulating antidepressants, have supported the theory confirmed this gene environment interaction (Rocha that dysfunctions of the 5-HT system are involved et al. 2015). The interactive effect of the S allele and in the pathogenesis of MDD (Jans et al. 2007). stress on the risk of MDD may be partly explained by Genetic polymorphisms are among the innate factors the modulation of the hypothalamo-pituitary-adrenal that modulate 5-HTergic neurotransmission, given that (HPA) axis. Indeed, S allele carriers display increased heritability has been reported to account for approxi- basal activity of the HPA axis and S/S homozygotes mately 35% of the variance in CSF 5-hydroxyindoleace- show increased cortisol/corticosterone stress reactivity tic acid (5-HIAA), the main metabolite of 5-HT levels compared with L carriers (van der Doelen et al. 2014). (Beck et al. 1984; Oxenstierna et al. 1986). Interesting findings from imaging studies include smaller hippocampal volumes in S carriers with a history of environmental adversities and higher amygdala 3.1. Serotonin transporter activity in response to a number of negative stimuli in The serotonin transporter (SERT) is the primary target S carriers (Won and Ham, 2016). In conclusion, the of selective serotonin reuptake inhibitors (SSRIs) and 5-HTTLPR S allele is considered to be a risk factor for one of the main targets of other antidepressant MDD but only in cases of stressful environmental con- classes. The SERT is responsible for 5-HT reuptake from ditions and it is neither a required nor sufficient factor the synaptic cleft and thus determines the magnitude for developing MDD. Insufficient data are available in and duration of the 5-HT synaptic signal. A reduction regard to the role of the triallelic locus (5-HTTLPR and of SERT sites in the brain (particularly in midbrain and rs25531 combination) in MDD susceptibility (Odgerel amygdala) of depressed patients has been demon- et al. 2013). strated both by functional imaging (Gryglewski et al. The triallelic 5-HTTLPR/rs25531 locus was also exten- 2014; Yeh et al. 2014) and post-mortem brain studies sively investigated as a modulator of antidepressant (Mann et al. 2000). As the binding to the SERT and the response. Single-photon emission computed tomog- 5-HT uptake capacity remain low after recovery, low raphy and positron emission tomography (PET) studies SERT activity has been suggested as a trait marker for reported that higher pre-treatment availability and mood disorders (Lesch 2001). greater SSRI occupancy of the SERT might predict

Table 1. Summary of genetic, epigenetic and mRNA/protein biomarkers of major depressive disorder and antidepressant response. 8 Gene Phenotype Polymorphism(s) and allele/genotype Epigenetic markers Peripheral biomarker References

SLC6A4 MDD 5-HTTLPR S allele environmental risk Elevated methylation may be Mixed findings Iga et al. (2005); Pena et al. (2005); Philibert et al. AL. ET FABBRI C. factors a proxy marker of child- (2008); Belzeaux et al. (2010); Olsson et al. (2010); hood adversities Karg et al. (2011); Booij et al. (2015) AD response 5-HTTLPR LL in Caucasian patients treated Mixed findings Higher platelet SERT affinity constant and higher Rausch et al. (2001); Rausch et al. (2002); Rausch et al. with SSRIs maximal uptake rate at baseline (2003); Fabbri et al. (2013a); Kang et al. (2013b); Myung et al. (2013); Belzeaux et al. (2014); Domschke et al. (2014); Okada et al. (2014) HTR1A MDD rs6295 G allele and GG genotype; rs878567 T NA Higher expression and binding Gonzalez et al. (2007); Kishi et al. (2013); Zhang et al. allele (2014) HTR2A MDD rs6311 A allele; rs6313 T allele; rs7997012 NA Platelet increased receptor density, but blunted Malone et al. (2007); Smith et al. (2013); Lin et al. GG; rs6313 in interaction with other SNPs receptor responsivity (2014); Zhao et al. (2014) of the region AD response rs6311 G allele NA Possible increase of HTR2A mRNA and 5-HT2A Belzeaux et al. (2010); Niitsu et al. (2013); Rivera-Baltanas receptor altered clustering et al. (2014) BDNF MDD rs6265 Met allele environmental risk Higher methylation of Decreased serum and plasma BDNF levels Fuchikami et al. (2011); D’Addario et al. (2013); Carlberg factors promoter/exon I et al. (2014); Dell’Osso et al. (2014); Hosang et al. (2014); Gutierrez et al. (2015); Januar et al. (2015); Polyakova et al. (2015) AD response Met/Val genotype in Asian subjects Mixed findings Increase in serum BDNF levels Brunoni et al. (2008); D’Addario et al. (2013); Kang et al. (2013a); Niitsu et al. (2013); Carlberg et al. (2014); Molendijk et al. (2014); Polyakova et al. (2015) CREB1 MDD Possible interaction with gender and BDNF NA Decreased CREB DNA binding activity, CREB total Zubenko et al. (2003); Utge et al. (2010); Juhasz et al. rs6265 protein expression and phosphorylated CREB (2011); Ren et al. (2011); Lim et al. (2013) AD response rs889895 GG and rs7569963 GG; possible NA Low baseline phosphorylated CREB, higher Koch et al. (2002); Lim et al. (2013) interaction with BDNF change of phosphorylated CREB GDNF MDD NA NA Decreased serum GDNF protein level Lin and Tseng (2015) AD response rs2973049 GG and CC preliminary evidence NA Increase in serum GDNF after antidepressant Zhang et al. (2008); Zhang et al. (2009) treatment CRP MDD rs1205 A preliminary evidence NA Increased serum levels Almeida et al. (2009); Howren et al. (2009); Valkanova et al. (2013); Wium-Andersen et al. (2013); Ancelin et al. (2015) AD response NA NA Decrease in serum level after AD treatment Hiles et al. (2012) IL-1b MDD rs16944 G allele NA Higher serum levels Howren et al. (2009); Borkowska et al. (2011); Mota et al. (2013) AD response rs16944 AA genotype NA Reduction in serum level after AD treatment; Yu et al. (2003); Tadic et al. (2008); Baune et al. (2010); lower mRNA level at baseline Hannestad et al. (2011); Belzeaux et al. (2012); Cattaneo et al. (2013) IL-6 MDD rs1800795 G allele (interferon-induced NA Higher serum levels Bull et al. (2009); Howren et al. (2009); Liu et al. (2012); depression) Udina et al. (2013); Valkanova et al. (2013) AD response rs7801617 NA Reduction in serum level after AD treatment Hiles et al. (2012); Yoshimura et al. (2013) TNF-a MDD rs76917 NA Higher serum levels Dowlati et al. (2010); Bosker et al. (2011); Liu et al. (2012) AD response NA NA Lower baseline mRNA and protein levels Belzeaux et al. (2012); Cattaneo et al. (2013); Powell et al. (2013) FKBP5 MDD rs1360780 T allele alone and x environmental Possible hypomethylation in One negative finding Lekman et al. (2008); Lavebratt et al. (2010); risk factors intron 7 region Szczepankiewicz et al. (2014); Zannas and Binder (2014); Hohne et al. (2015) AD response rs1360780 TT genotype NA Reduction in mRNA levels Cattaneo et al. (2013); Niitsu et al. (2013); Fabbri and Serretti (2015) SLC6A4, serotonin transporter; MDD, major depressive disorder; AD, antidepressant; HTR1A, serotonin receptor 1A; NA, no data available; HTR2A, serotonin receptor 2A; BDNF, brain-derived neurotrophic factor; CREB1, cyclic AMP response element binding protein 1; GDNF, glial cell line-derived neurotrophic factor; CRP, C-reactive protein; IL-1b, interleukin-1b; IL-6, interleukin-1b; TNF-a, tumour necrosis factor alpha; FKBP5, FK506- binding protein 52 or FKBP51. THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 9

Table 2. Biomarkers used by pilot studies investigating predictors of MDD diagnosis and antidepressant response for clinical applicability. Phenotype Biomarkers Main findings References AD treatment out- CYP2D6, CYP2C19, CYP2C9, CYP1A2, SLC6A4 Higher disability and costs in patients identi- Hall-Flavin et al. (2013); comes (response, and HTR2A polymorphisms fied as ‘‘at risk’’ by the test; better Winner et al. (2013a, 2015) disability and costs) response when the test is used to guide treatment AD efficacy ABCB1 rs2032583 and rs2235015 Higher remission rates and lower symptom Breitenstein et al. (2014) severity at the time of discharge from hospital when the test is used to guide treatment AD efficacy FKBP5 rs1360780 Worse treatment outcome in C allele carriers Stamm et al. (2016) in the treatment as usual arm compared to the genotype-guided arm AD treatment out- CYP2D6, CYP2C19, CYP3A4, SLC6A4, HTR2C, Not clear improvement in response or remis- Brennan et al. (2015); comes (response, DRD2, CACNA1C, ANK3, COMT, MTHFR, sion rates, higher medication adherence Fagerness et al. (2014) treatment adher- MC4R, ADRA2A, BDNF, OPRM1 and GRIK1 and cost savings when the test is ence, costs) polymorphisms performed AD efficacy CYP2D6, CYP2C19, UGT1A1, ABCB1 and Higher remission when the test is used to Singh (2015) ABCC1 polymorphisms guide treatment MDD diagnosis Serum alpha1 antitrypsin, apolipoprotein CIII, Overall test accuracy of 91–94% in distin- Papakostas et al. (2013); BDNF, cortisol, epidermal growth factor, guishing patients from controls Bilello et al. (2015) myeloperoxidase, prolactin, resistin and soluble TNF-a receptor type II better treatment response (Kugaya et al. 2004; Yeh and associated with family history of depression and et al. 2015). The most confirmed pharmacogenetic more severe depressive psychopathology (Kang et al. finding was an association of the S allele with worse 2013b). Another recent study found no evidence of an antidepressant efficacy than the LL genotype in effect of increased SLC6A4 methylation status on the Caucasian patients treated with SSRIs (Porcelli et al. risk of MDD (Okada et al. 2014). These findings support 2012). Relatively fewer studies genotyped the triallelic the hypothesis that SLC6A4 methylation status may be locus and they did not support a substantial role of a proxy of childhood adversities (other than a heredi-

the polymorphism on antidepressant efficacy (Fabbri tary factor) and thus it may be a useful marker of MDD et al. 2013a). Several pharmacogenetic studies (Perlis susceptibility in combination with the 5-HTTLPR S et al. 2003; Murphy et al. 2004; Popp et al. 2006; allele. SLC6A4 methylation status was also investigated Hu et al. 2007; Smits et al. 2007; Maron et al. 2009) in relation to antidepressant treatment response, but and one meta-analysis (Kato and Serretti 2010) with mixed results (Kang et al. 2013b; Domschke et al. reported that the S allele may also be a risk factor for 2014; Okada et al. 2014). the development of SSRI-induced side effects in Caucasian populations, though not for sexual dysfunc- 3.1.3. Peripheral biomarkers tion (Bishop et al. 2009; Strohmaier et al. 2011). The genetic and epigenetic modulation of SERT expression and function has been complemented by the 3.1.2. Gene methylation study of SERT as a peripheral biomarker of MDD and DNA methylation profiles at CpG (cytosine-guanine antidepressant efficacy. SERT functioning can be dinucleotides) islands have been studied as a modula- studied in platelets, since the SERT protein expressed tor of SLC6A4 expression. Indeed, methylation at CpG in platelets is considered identical to the one found in islands make a gene less accessible to the molecular neurons, with similar structural and functional proper- transcriptional apparatus that decodes the DNA ties found in both tissues (Yubero-Lahoz et al. 2013). sequence into mRNA and hence the production of spe- Higher SERT affinity constant and higher maximal cific proteins is reduced. An early study found a trend uptake rate before and after antidepressant treatment of association between history of MDD and increased were associated with treatment efficacy (Rausch et al. SLC6A4 methylation (Philibert et al. 2008), and a subse- 2001, 2002, 2003; Myung et al. 2013). Interestingly, quent study reported that depressive symptoms were reductions in peripheral cell 5-HT uptake rates, cell sur- more common among adolescents with elevated face SERT binding, and 5-HIAA/serotonin ratios were SLC6A4 methylation who carried the 5-HTTLPR S allele associated with the 5-HTTLPR S allele, suggesting that (Olsson et al. 2010). Higher SLC6A4 promoter methyla- they may represent proxy markers of the 5-HTTLPR tion in subjects with a history of childhood adversities genotype (Singh et al. 2012). SLC6A4 expression was demonstrated (Kang et al. 2013b; Booij et al. 2015) (mRNA level) in peripheral cells (lymphocytes) was also 10 C. FABBRI ET AL. investigated, since lymphocytes are thought to poten- controls, confirming the hypothesis derived from func- tially act as a neural probe for studying psychiatric dis- tional studies. The study also found that rs878567 (syn- orders (Gladkevich et al. 2004). Studies on small onymous SNP located downstream of the gene) T samples of depressed patients suggested a reduction allele was associated with MDD susceptibility (Kishi of SERT expression after antidepressant treatment (Iga et al. 2013). The most recent meta-analyses that inves- et al. 2005; Tsao et al. 2006) with a possible positive tigated the role of rs6295 in antidepressant efficacy correlation with response (Belzeaux et al. 2014), but provided negative findings (Zhao et al. 2012; Niitsu opposite findings also exist (Pena et al. 2005; Belzeaux et al. 2013). Other polymorphisms in the gene were et al. 2010). The reduction of SERT expression in the marginally investigated. rat brain was associated with antidepressant-like behaviours (Thakker et al. 2005) and key markers of 3.2.1.2. Peripheral biomarkers Higher platelet HTR1A antidepressant action: reduced expression and function expression was associated with MDD and severity of of 5-HT1A-autoreceptors, elevated extracellular 5-HT in symptoms in drug-free patients (Zhang et al. 2014), the forebrain and increased neurogenesis and expres- and higher receptor binding was found in lymphocytes sion of plasticity-related genes (BDNF, VEGF, ARC)in of depressed patients (Gonzalez et al. 2007). In con- the hippocampus (Ferres-Coy et al. 2013). No clear trast, a previous study did not report any difference in association between SLC6A4 expression and MDD risk lymphocyte 5-HT1A receptor capacity and affinity was demonstrated, since the few studies reported between MDD patients and controls (Fajardo et al. either negative findings (Belzeaux et al. 2010), higher 2003). No data are available in regard to antidepres- expression of the gene in patients compared to con- sant efficacy. trols (Iga et al. 2005) or the opposite finding (Pena et al. 2005). 3.2.2. Serotonin receptor 2A The serotonin receptor 2A (5-HT2A) is primarily a post- 3.2. Serotonin receptors synaptic excitatory receptor, with wide distribution throughout the brain but with the highest density in 3.2.1. Serotonin receptor 1A the neocortex (Burnet et al. 1995). Both depression

The 5-HT1A autoreceptor mediates the inhibition of and suicide have been associated with greater 5-HT2A serotonergic raphe neurons by negative feedback receptor binding in PFC, although data were not con- (Pineyro and Blier 1999), while 5-HT1A postsynaptic sistent (Stein et al. 2007). Accordingly, there is a receptor activation has been shown to increase dopa- decrease in 5-HT2A binding in cortical regions, particu- mine release in the medial prefrontal cortex (PFC), stri- larly in the frontal cortex, after antidepressant treat- atum and hippocampus (Sakaue et al. 2000). These ment (Meyer et al. 2001), and compensatory findings suggest that increased 5-HT1A presynaptic downregulation of 5-HT2A receptors can prevent and decreased postsynaptic activity may co-occur in depressive symptoms induced by tryptophan depletion MDD. Several studies using PET imaging demonstrated (Yatham et al. 2001). elevated 5-HT1A binding in the brain of MDD subjects, especially in the raphe (Parsey et al. 2010; Kaufman 3.2.2.1. Genetic polymorphisms Different polymor- et al. 2015). 5-HT1A density distinguished male controls phisms (rs6311 or -1438A/G, rs6313 or 102C/T, from depressed males with high sensitivity and specifi- rs7997012 and rs7333412) have been investigated city (both >80%) (Kaufman et al. 2015). A reduction in within the 5-HT2A gene with several positive but often raphe 5-HT1A autoreceptor binding was demonstrated inconsistent findings (Polesskaya and Sokolov 2002; Lin during SSRI treatment and was associated with symp- et al. 2009; Fabbri et al. 2013b; Niitsu et al. 2013; Zhao tom improvement (Gray et al. 2013). et al. 2014). Interestingly, the region downstream to the first intron of the gene was found to harbour other 3.2.1.1. Genetic polymorphisms The G allele of a func- possibly relevant polymorphisms in the context of anti- tional promoter polymorphism in the serotonin 1A depressant response. Indeed, rs7333412, rs7324017, receptor gene (HTR1A rs6295 or C-1019G) has been rs1923882 (Fabbri et al. 2014) and rs7997012 (Peters associated with increased 5-HT1A expression in raphe et al. 2009) are located in this region and were associ- nucleus neurons both in vitro (Lemonde et al. 2003) ated with antidepressant response in the STAR*D sam- and in vivo using PET (Parsey et al. 2010). A recent ple. Several other studies investigated rs7997012 with meta-analysis found that MDD patients had higher fre- negative results (Illi et al. 2009; Kishi et al. 2009; Perlis quencies of the GG genotype and/or G allele than et al. 2009; Uher et al. 2009; Horstmann et al. 2010), THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 11 although none of these included samples as large as Integrins are involved in the control of synaptic plasti- the STAR*D study. The effect of rs7997012 and rs6313 city and long-term potentiation (Martins-de-Souza et al. on antidepressant efficacy was confirmed by the most 2014). recent meta-analysis (Lin et al. 2014). 4.1. Brain-derived neurotrophic factor 3.2.2.2. Peripheral biomarkers Platelet 5-HT2A binding kinetics did not differ between MDD patients and con- Brain-derived neurotrophic factor (BDNF) is included in trols (Khait et al. 2005), but seasonal variation in plate- the neurotrophin family of growth factors and acts as let 5-HT2A binding was demonstrated to be different an important mediator of neuron survival, neuroplastic- in MDD patients compared to controls (Khait et al. ity and neurogenesis. BNDF is implicated in processes 2002). Increased density of platelet 5-HT2A receptors that modulate learning, memory and mood (Soule may be a marker of MDD, but is more consistently et al. 2006; Cowansage et al. 2010). Stress was demon- associated with suicide risk (Mendelson, 2000). Despite strated to decrease BDNF in mouse hippocampus, cor- increased receptor density, blunted receptor response tical and subcortical regions (Pizarro et al. 2004). was found in patients who have made high-lethality Antidepressant treatment increases BDNF levels, stimu- suicide attempts (Malone et al. 2007). Preliminary evi- lates neurogenesis and reverses the inhibitory effects dence suggested that a trend of increased HTR2A of stress, thus BDNF and neurotrophins are possible mRNA levels in peripheral lymphocytes may be targets for developing new antidepressant molecules observed during the first 8 weeks of antidepressant (Masi and Brovedani 2011). treatment (Belzeaux et al. 2010), suggesting that further studies should investigate this potential biomarker 4.1.1. Genetic polymorphisms of antidepressant efficacy. Another preliminary study found that 5-HT2A receptor clustering in peripheral The common SNP rs6265 (Val66Met or 196G/A) of the lymphocytes is altered in MDD and may be a bio- BDNF gene has received particular attention, since the marker of therapeutic efficacy (Rivera-Baltanas et al. Met allele decreases the processing and release of 2014). BDNF and is associated with decreased hippocampal

volume in humans. However, available data do not support a significant effect of rs6265 on MDD suscepti- 4. Neuroplasticity bility, as indicated by meta-analyses (Gratacos et al. Neural plasticity may be defined as the ability of neu- 2007; Gyekis et al. 2013) that also provided negative rons and neural elements to adapt in response to findings for other BDNF SNPs (11757C/G, 270T/C, 712A/ intrinsic and extrinsic signals. Adult neurogenesis, the G and rs988748). Conversely, the rs6265 Met allele was development of dendritic spines, and synaptic adapta- demonstrated to moderate the relationship between tions are included among the processes defined as life stress and depression (Hosang et al. 2014; Gutierrez neural plasticity. Adult hippocampal neurogenesis has et al. 2015). been hypothesised to play a key role in the pathogen- Pharmacogenetic studies of antidepressant response esis and successful treatment of MDD (Wainwright and mainly found a positive molecular heterosis effect of Galea 2013). Indeed, depressed patients have reduced the rs6265 SNP. Indeed, the rs6265 heterozygous geno- hippocampal volume and neurogenesis that is influ- type was associated with better treatment outcome as enced by the number of episodes and duration of the confirmed by a recent meta-analysis (Niitsu et al. illness (McKinnon et al. 2009; Wainwright and Galea 2013), although some inconsistent or negative findings 2013). Antidepressant drugs can both prevent stress- were also reported (Fabbri et al. 2013a). induced decrease of hippocampal neurogenesis and reverse it (Malberg and Duman 2003; Bessa et al. 4.1.2. Gene methylation 2009). Pathway analysis confirmed the enrichment of neuroplasticity pathways in MDD, with the involvement Hypermethylation of the BDNF gene promoter was of CREB signalling in neurons, synaptic long-term reported in Wernicke’s area (Keller et al. 2010) and per- potentiation and axonal guidance signalling (Jia et al. ipheral blood (Kang et al. 2013a) of subjects who com- 2011; Hunter et al. 2013). Interestingly, several mem- mitted suicide. The CpG island of the BDNF gene bers of the integrin signalling pathway, including upstream of exon I was found as a possible diagnostic ITGB3, ZYX, ARF1, CAPNS1, CDC42, ILK, LIMS1, RAC2 biomarker of MDD (Fuchikami et al. 2011), and higher and TTN were found differentially expressed between methylation status of the BDNF promoter was associ- antidepressant responders and non-responders. ated with MDD (D’Addario et al. 2013; Carlberg et al. 12 C. FABBRI ET AL.

2014; Dell’Osso et al. 2014; Januar et al. 2015) and hippocampus of rats (Ignacio et al. 2014). As a result of post-stroke depression (Kim et al. 2013). such findings, CREB1 is hypothesised to upregulate the Lower histone 3 lysine 27 (H3K27) trimethylation transcription of BDNF, representing an important binding within the BDNF promoter (P4 region) of PFC mechanism of action of antidepressants. (Chen et al. 2011) and peripheral blood (Lopez et al. 2013) was associated with antidepressant treatment, 4.2.1. Genetic polymorphisms and with positive response to treatment (Lopez et al. CREB1 polymorphisms have been associated with 2013). The effect of antidepressant drugs on BDNF pro- mood disorders, mainly exhibiting a significant gender moter methylation levels is still scarcely investigated effect (Zubenko et al. 2003a, 2003b; Perlis et al. 2007; and available data suggested a possible higher methy- Dong et al. 2009; Utge et al. 2010; Juhasz et al. 2011; lation status in treated versus untreated patients Lazary et al. 2011), nevertheless not unequivocally (Carlberg et al. 2014), but an enhanced reduction in (Burcescu et al. 2005; Hettema et al. 2009). Findings for suicidal ideation after treatment in subjects with low CREB1 and antidepressant response are also inconsist- methylation levels (Kang et al. 2013a). Methylation lev- ent (Murphy et al. 2004; Wilkie et al. 2007; Serretti els may also be reduced in patients receiving combin- et al. 2011; Calati et al. 2013) and negative findings ation treatments of antidepressants plus mood have also been reported (Dong et al. 2009; Crisafulli stabilisers compared to patients on antidepressant et al. 2012; Matsumoto et al. 2014). drugs alone (D’Addario et al. 2013). 4.2.2. Peripheral biomarkers 4.1.3. Peripheral biomarkers CREB DNA binding activity, CREB total protein expres- According to recent meta-analytic results, both serum sion and phosphorylated CREB were found decreased and plasma BDNF levels are decreased in acute MDD, in leukocytes of drug-free MDD patients compared but do not differ in euthymic subjects with a history of with normal controls (Ren et al. 2011; Lim et al. 2013). MDD compared to healthy controls. Furthermore, anti- On the other hand, no difference in mRNA levels depressant treatment of MDD patients increases serum between patients and controls was demonstrated by BDNF levels in responders and remitters significantly other studies in small samples of MDD patients (Lai more than in non-responders, but insufficient data are et al. 2003; Belzeaux et al. 2010; Iacob et al. 2013). available for comparing plasma levels in responders Another study focussed on mRNA levels in leukocytes versus non-responders (Polyakova et al. 2015). This demonstrated an opposite finding, i.e., higher CREB would be an important comparison, as plasma and mRNA levels in MDD patients compared to controls serum BDNF levels show at least a 100-fold difference (Iga et al. 2007). We underline that negative findings (Rosenfeld et al. 1995). The results of prior meta-analy- were restricted to gene expression studies that did not ses reported similar results. Their analyses demon- consider CREB DNA binding activity and protein levels, strated lower serum BDNF concentrations in and were therefore unable to identify possible conse- antidepressant-free depressed patients relative to both quences of abnormalities during or after mRNA transla- healthy controls and antidepressant-treated depressed tion into proteins. patients (Brunoni et al. 2008; Molendijk et al. 2014) Animal models (Tardito et al. 2009) and in vitro data and an increase in BDNF levels after antidepressant (Hisaoka et al. 2008) support the induction of CREB treatment that was associated with the degree of activation and CREB-regulatory signalling by antide- symptom improvement (Brunoni et al. 2008). pressants. Patients with low baseline phosphorylated CREB in peripheral T lymphocytes showed a greater rate of response than patients with high baseline phos- 4.2. Cyclic AMP response element binding phorylated CREB. A value of baseline phosphorylated protein 1 CREB for predicting response was identified by Hisaoka Cyclic AMP response element binding protein 1 et al. (2008) who reported a positive predictive value (CREB1) encodes a transcription factor that induces of 0.78, a negative predictive value of 0.64 and accur- transcription of genes in response to hormonal stimu- acy of 0.695. After 6 weeks of SSRI treatment, median lation of the cAMP pathway. Chronic treatment with values of change of both total and phosphorylated SSRIs increased the expression of phosphorylated CREB were greater in responders than in non-respond- CREB1 in the hippocampus and PFC of rats, and treat- ers (Lim et al. 2013). A greater increase in phosphory- ment with antidepressants also increased the levels of lated CREB in responders was confirmed by other protein and mRNA of CREB1 and BDNF in the studies using different pharmacological or THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 13 psychotherapeutic treatments (Koch et al. 2002, 2009), regulation of neuroendocrine response to stress, influ- but no variation was reported after venlafaxine treat- ence the availability of monoamine neurotransmitters, ment (Rojas et al. 2011). Inconsistent findings were and decrease neurogenesis. Conversely, both medically reported in regard to CREB1 mRNA variations after ill and medically healthy patients with MDD have been antidepressant treatment (increased, Belzeaux et al. found to exhibit elevations in inflammatory cytokines 2010, or decreased, Lai et al. 2003; Iga et al. 2007, and their soluble receptors in peripheral blood and levels). CSF, as well as elevations in peripheral blood concentrations of acute phase proteins, chemokines, adhesion molecules and inflammatory mediators such as prosta- 4.3. Glial cell line-derived neurotrophic factor glandins (Miller et al. 2009). A proteomic analysis in Glial cell line-derived neurotrophic factor (GDNF) is a patients with MDD compared to controls confirmed member of the transforming growth factor beta super- that altered expression proteins involve lipid metabol- family and is extensively distributed in mammalian ism and inflammation (Xu et al. 2012). A comprehen- brains, including the hypothalamus, substantia nigra sive analytical framework based on multiple lines of and thalamus (Golden et al. 1998). GDNF promotes evidence including association, linkage, gene expres- neurite growth (Ducray et al. 2006) and protects neu- sion, regulatory pathways and literature searches fur- rons and glial cells from oxidative or neuro-inflamma- ther support the role of inflammatory pathways in tory injury (Hochstrasser et al. 2011; Jaumotte and MDD (Jia et al. 2011). Zigmond 2014).

4.3.1. Genetic polymorphisms 5.1. C-reactive protein To the best of our knowledge, only one previous study C-reactive protein (CRP) is a marker of systemic inflam- investigated the possible impact of GDNF genetic poly- mation and CRP phenotypes are 40% heritable, a morphisms on antidepressant response and no study hereditability similar to that for major depression (Su investigated the possible effect on MDD susceptibility. et al. 2009). Environmental factors such as smoking, In detail, rs2973049 A allele and rs2216711 T allele obesity and cardiovascular diseases, as well as gender were associated with paroxetine non-response in a differences could also be implicated and modulate the Chinese population (Wang et al. 2014), the latter show- relationship between the CRP gene and depression ing a selective effect in females. (Hage and Szalai 2009). This may be especially important in the elderly who have a high prevalence of 4.3.2. Peripheral biomarkers comorbid chronic disorders. Recent meta-analytic findings supported a moderate but significant decrease in serum GDNF protein level in 5.1.1. Genetic polymorphisms patients with depression, with a selective effect on Several genetic polymorphisms in the CRP gene MDD that was not observed in other depressive disor- have been associated with CRP levels (Almeida et al. ders nor in old-age depression (Lin and Tseng 2015). A 2009), but their association with depression remains decrease in serum GDNF protein level was also found controversial (Almeida et al. 2009; Halder et al. 2010; in adolescent depression (Pallavi et al. 2013), but meta- Luciano et al. 2010; Gaysina et al. 2011; Ancelin et al. analytic data are unavailable to support this finding. 2015). GDNF mRNA in peripheral cells was reduced in individuals during a major depressive episode compared to 5.1.2. Peripheral biomarkers individuals in remission and to healthy controls (Otsuki et al. 2008). Furthermore, an increase in serum GDNF High CRP serum levels were identified as a risk factor concentrations was demonstrated after antidepressant for de novo depression in women (Pasco et al. 2010), pharmacological treatment (Zhang et al. 2008) and depression in men (Ford and Erlinger, 2004; Liukkonen electroconvulsive therapy (Zhang et al. 2009). et al. 2006; Elovainio et al. 2009; Vogelzangs et al. 2012), atypical depression (Hickman et al. 2014) and depressive symptoms (Uddin et al. 2011), especially of 5. Inflammation and HPA axis the somatic type (Duivis et al. 2013). Furthermore, life- Bi-directional mechanisms have been hypothesised to time occurrence of multiple depressive episodes was link inflammatory processes and depression. Prolonged associated with higher CRP levels (Copeland et al. exposure to inflammatory mediators can impair the 2012). In a very large cohort of more than 70, 000 14 C. FABBRI ET AL. individuals, cross-sectional analysis demonstrated that et al. 2011). However, one meta-analysis investigated increased CRP levels were associated with increased the role of IL-1b serum level in major depression and risk for psychological distress and depression (Wium- reported no evidence of association (Dowlati et al. Andersen et al. 2013). Two meta-analyses have con- 2010). The latter meta-analysis included fewer studies firmed that major depression is associated with compared to the work of Howren et al. (2009) though increased CRP levels (Howren et al. 2009; Valkanova the study did take into account potential confounders et al. 2013). (e.g., BMI, type of depression assessment). More recent The majority of studies demonstrated a reduction in studies found that serum levels of IL-1b were higher in CRP serum level after SSRI treatment (Leo et al. 2006; MDD when compared to controls or bipolar disorder O’Brien et al. 2006; Pizzi et al. 2009) and treatment subjects (Mota et al. 2013) and IL-1b mRNA was identi- with non-SSRI antidepressants (Lanquillon et al. 2000; fied as a possible marker for predicting antidepressant Tuglu et al. 2003). A single study reported opposite response (Belzeaux et al. 2012). The latter finding was findings (Dawood et al. 2007). A meta-analysis reported confirmed by an independent study that found higher a marginally significant decrease in CRP after anti- baseline mRNA levels of IL-1b (þ33%) in non-respond- depressant treatment (Hiles et al. 2012), while higher ers (Cattaneo et al. 2013). Platelet content of IL-1b was CRP levels at baseline were found to predict the per- also associated with MDD (Hufner et al. 2014). sistence of depressive symptoms over 5 years (Zalli et al. 2015). Interestingly, MDD patients with high CRP levels were also reported to be less placebo-responsive 5.3. Interleukin-6 and less responsive to eicosapentaenoic acid (EPA; Interleukin-6 (IL-6) is a pleiotropic pro-inflammatory Rapaport et al. 2015). cytokine, whose peripheral concentration was found to be inversely related to hippocampal volume in MDD 5.2 Interleukin-1b (Frodl et al. 2012). The pathogenetic role of IL-6 in depression involves the acute phase of response, disor- Interleukin-1b (IL-1b) is a potent pro-inflammatory ders in zinc and the erythron, HPA axis activation, cytokine that acts as a key driver of both peripheral induction of the tryptophan catabolite pathway, oxida- and central immune responses. IL-1b has been exten- tive stress, autoimmune processes and neuroprogres- sively described for its ability to act within the CNS as sion (Maes et al. 2014). a modulator of hippocampal memory, as well as for its involvement in neuronal death (van de Veerdonk and 5.3.1. Genetic polymorphisms Netea 2013). IL-1b was demonstrated to regulate the activity of key members of the kynurenine pathway IL-6 polymorphisms were mainly studied in relation to with an effect on the availability of tryptophan and the specific subtypes of depression, such as post-stroke production of toxic metabolites, explaining its modulat- depression (Kim et al. 2012) and childhood depression ing effect on neurogenesis in human hippocampal pro- (Misener et al. 2008), but with negative findings. The - genitor cells (Zunszain et al. 2012). 174 SNP (rs1800795) is particularly interesting since individuals who carry the G allele have higher plasma 5.2.1. Genetic polymorphisms concentrations of IL-6 (Zakharyan et al. 2012) and the polymorphism has been studied as a modulator of The G allele of the rs16944 polymorphism (located interferon-induced depression. Patients who carried within the promoter of the IL-1b gene) has been asso- the C allele (low synthesising IL-6) were reported to ciated with SSRI non-response (Yu et al. 2003; Tadic show fewer depressive and anxiety symptoms than et al. 2008; Baune et al. 2010) and with recurrent major those carrying the G allele, after beginning treatment depression (Borkowska et al. 2011). In addition, IL-1b with IFN-a (Bull et al. 2009; Udina et al. 2013). promoter polymorphism rs1143627 was also associated However, only a small study investigated the potential with recurrent major depression (Borkowska et al. role of the SNP in MDD and it reported negative find- 2011). ings (Clerici et al. 2009), while an additional study reported no association between MDD and the SNP at 5.2.2. Peripheral biomarkers -634 in a Chinese population (Hong et al. 2005). Our Meta-analyses reported both a positive association findings suggest further investigation of IL-6 polymor- between IL-1b serum level and depression (Howren phisms in MDD is warranted, particularly as a suggest- et al. 2009), in addition to a reduction in IL-1b serum ive signal (rs7801617 SNP) for association with level following antidepressant treatment (Hannestad escitalopram response was detected in the IL-6 gene in THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 15 the Genome-Based Therapeutic Drugs for Depression theory of depression, the A allele was associated with (GENDEP) genome-wide association study (Uher et al. a higher risk of MDD in Korean subjects (Jun et al. 2010). 2003), but later studies either found no association with post-stroke depression (Kim et al. 2012) and sin- 5.3.2. Gene methylation gle-episode depression (Haastrup et al. 2012), or reported a positive association in the opposite direc- An inverse correlation between methylation of IL-6 tion in late-life depression (Cerri et al. 2009). However, CpGs and circulating IL-6 and CRP levels was reported these studies were performed on small sample sizes in individuals with lifetime depression (Uddin et al. and limited coverage of genetic variability was pro- 2011), but findings have yet to be replicated. vided. Importantly, the Genetic Association Information Network genome-wide association study (1738 cases 5.3.3. Peripheral biomarkers and 1802 controls) found the rs76917 variant showed Two meta-analyses supported the association between the strongest evidence of association with MDD MDD and higher IL-6 levels compared to healthy con- (Bosker et al. 2011), suggesting that studies with trols (Howren et al. 2009; Liu et al. 2012). Furthermore, adequate sample size and sufficient gene coverage one meta-analysis of longitudinal studies reported a have increased power to demonstrate the influence of modest effect of IL-6 levels on the risk of developing TNF-a on MDD. No pharmacogenetic studies are avail- subsequent depressive symptoms (Valkanova et al. able investigating the possible association between 2013). A pathway analysis on transcriptomic data TNF-a polymorphisms and antidepressant response. showed that genes upregulated in MDD subjects compared to controls were enriched in IL-6 signalling path- 5.4.2. Peripheral biomarkers ways (Jansen et al. 2016). Meta-analytic results reported that TNF-a blood levels Meta-analytic results also suggested a significant are higher in MDD compared to healthy controls decrease in IL-6 serum levels after antidepressant treat- (Dowlati et al. 2010; Liu et al. 2012), especially in sub- ment (Hiles et al. 2012), as confirmed by a subsequent jects of European ancestry (Liu et al. 2012). TNF-a study that demonstrated a correlation between plasma mRNA levels in peripheral leukocytes were also found IL-6 levels and changes in severity of depressive state to be higher in patients with major depression com- during SSRI treatment (Yoshimura et al. 2013). MDD pared to controls (Tsao et al. 2006). patients with high IL-6 levels were also reported to be Higher baseline levels of TNF-a mRNA and protein less placebo responsive and less responsive to EPA were associated with non-response in the GENDEP pro- (Rapaport et al. 2015). IL-6 mRNA levels at baseline or ject (Cattaneo et al. 2013; Powell et al. 2013) and find- after antidepressant treatment were not found to be ings in the inflammatory cytokine pathway at baseline associated with response in the GENDEP project and after antidepressant treatment were found to be (Cattaneo et al. 2013; Powell et al. 2013). targets of TNF (Powell et al. 2013). TNF-a mRNA levels at baseline were proposed as predictive of antidepres- 5.4. Tumor necrosis factor alpha sant response in conjunction with three other mRNAs (PPT1, IL-1b and HIST1H1E) (Belzeaux et al. 2012). A Tumor necrosis factor alpha (TNF-a) is a pro-inflamma- meta-analysis antecedent to these studies found no tory cytokine that is hypothesised to contribute to clear evidence of reduction in TNF-a serum levels after the development of MDD and is involved in the antidepressant treatment, but found some evidence modulation of serotonergic neurotransmission through that SSRIs may reduce TNF-a serum levels (Hannestad the increase of SERT expression and activity et al. 2011). (Malynn et al. 2013). Mice susceptible to stress-induced anhedonia show elevated expression of TNF-a and SERT in the prefrontal area (Couch et al. 2013) and 5.5. FK506-binding protein 52 or 51 SSRIs inhibit the secretion of TNF-a in human T lym- The FKBP5 (FK506-binding protein 52 or FKBP51) gene phocytes (Taler et al. 2007). encodes for a member of the family of large immuno- philins. The encoded protein was reported to act as a 5.4.1. Genetic polymorphisms scaffolding protein regulating Akt activity that might The G-308A (rs1800629) TNF-a polymorphism is a func- have implications in the development and treatment tional SNP whose A allele is associated with higher of depression (Duman and Voleti 2012). The FKBP51 gene expression. Consistent with the inflammatory protein is a co-chaperone for glucocorticoid receptor 16 C. FABBRI ET AL.

(GR) maturation, modulating its sensitivity and thus et al. 2004). Furthermore, rs352428 was demonstrated playing a role in the regulation of stress response. to be a functional polymorphism that may alter tran- Further supporting this notion are studies showing scription factor binding (Ellsworth et al. 2013) and thus that increased expression of the FKBP5 gene confers gene expression. elevated GR resistance (Binder, 2009) and that gluco- corticoids induce FKBP5 expression (Vermeer et al. 5.5.2. Gene methylation 2003). Rats exposed to chronic mild stress show DNA methylation in the rs1360780 region in intron 7 increased expression of FKBP5 as well as enhanced of FKBP5 showed a non-significant trend toward geno- cytoplasmic levels of GR, primarily in ventral hippocam- type-dependent CpG methylation differences (hypome- pus and PFC. Chronic treatment with the antidepres- thylation) among subjects with a lifetime history of sant duloxetine is able to normalise such alterations MDD (Hohne et al. 2015). Consistently, exposure to (Guidotti et al. 2013). child abuse leads to a significant demethylation of 5.5.1. Genetic polymorphisms CpGs in the functional glucocorticoid response elements (GREs) in intron 7 of the FKBP5 gene. A number of studies reported an FKBP5 environment Demethylation of these CpGs leads to an enhanced interaction in predicting the risk of depression, which induction of FKBP5 transcription by GR agonists and is is consistent with the observation that FKBP5 is respon- associated with GR resistance (Klengel et al. 2013). The sive to stressor exposure and increases glucocorticoid exposure to stressful events during childhood is levels by modulating GR sensitivity (Zannas and Binder hypothesised to induce local CpG demethylation medi- 2014). More precisely, rs9296158, rs4713916, ated by GR binding to GREs, followed by a depressed rs1360780, rs9470080 and rs3800373 have been found transcriptional response to subsequent glucocorticoid to be involved in gene childhood trauma interac- exposure. Thus, stressor exposure results in higher cor- tions, likely through mediating epigenetic modifica- tisol release and GR activation in rs1360780 risk allele tions (see Section 4.5.2). The rs1360780 T allele was carriers (Zannas and Binder, 2014). identified as the risk allele by three studies, the Of interest, the spindle and kinetochore complex rs9470080 T allele by two studies, and the rs3800373 C subunit 2 (SKA2) protein is similar to FKBP51, in that it allele by one study (Zannas and Binder 2014). Some interacts with the GR. The C allele of the SKA2 genetic studies did not take into account FKBP5 environ- polymorphism rs7208505 (C/T) can be epigenetically ment interactions and three studies found that the modified via addition of a methyl group. The combin- rs1360780 T allele was associated with increased risk of ation of genetic variation and epigenetic modification depression (Lekman et al. 2008; Lavebratt et al. 2010; at rs7208505 has been associated with MDD and sui- Szczepankiewicz et al. 2014), two studies found an cide and this finding has been replicated in both post- effect of rs4713916 (Zobel et al. 2010; Szczepankiewicz mortem brain tissue and peripheral blood samples et al. 2014), and non-replicated findings were reported (Guintivano et al. 2014). for rs9470080, rs9296158 (Szczepankiewicz et al. 2014) and rs3800373 (Zobel et al. 2010). 5.5.3. Peripheral biomarkers Despite controversial pharmacogenetic findings being reported for the FKBP5 gene, results obtained in In healthy subjects the rs1360780 CC genotype showed a large sample of Caucasian subjects suggested that an increase of FKBP5 mRNA levels after stress exposure rs1360780, rs3800373, rs4713916 and rs352428 poly- compared to CT or TT genotypes, despite no genotype morphisms may modulate antidepressant response effect on mRNA expression found in remitted MDD (Fabbri and Serretti, 2015). The effect of rs3800373 and patients (Hohne et al. 2015). A reduction in FKBP5 rs1360780 on antidepressant response was confirmed mRNA levels after 8 weeks of antidepressant treatment in subjects of Caucasian ethnicity by a recent was associated with successful antidepressant response meta-analysis (Niitsu et al. 2013). Interestingly, (Cattaneo et al. 2013). rs1360780 TT genotype showed FKBP5 protein levels that were twice as high as C allele carriers in vitro 6. Clinical applications: pilot studies (Binder et al. 2004). This genotype was associated with faster response, modulation of FKBP5 expression, lower Evaluation of the reliability versus cost/effectiveness ACTH response in the combined dexamethasone-sup- ratio of using biomarkers in clinical settings is a crit- pression/CRH-stimulation test and, hypothetically, a ical phase for the translation of research into tailored faster restoration of normal HPA axis function (Binder treatments. Studies are investigating the clinical THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 17 usefulness of genetic testing for the prediction of in ABCB1, the gene encoding for the P-glycoprotein (or antidepressant treatment outcome, in addition to P-gp). P-gp is an ATP-dependent drug efflux pump for serum-based tests analysing the expression levels of xenobiotic compounds which limits uptake and accu- nine genes proposed for use in MDD diagnosis. mulation of some lipophilic drugs (including several Genetic tests for use in predicting antidepressant antidepressants) into the brain. In the genotype-guided response include genes involved in antidepressant treatment arm ABCB1 gene test results (rs2032583 and metabolism (the cytochrome P450 (CYP) superfamily; rs2235015 SNPs) were implemented into the clinical Porcelli et al. 2011), antidepressant transport (ABCB1) decision making process and this group showed higher and antidepressant drug targets. For example, the remission rates and lower symptom severity at the GeneSight assay was designed to predict antidepres- time of discharge from hospital as compared to sant response and side effects on the basis of poly- patients without ABCB1 testing (Breitenstein et al. morphisms in CYP2D6, CYP2C19, CYP2C9, CYP1A2, 2014). Furthermore, antidepressant dose adjustments SLC6A4 and HTR2A. Patients classified as ‘‘at risk’’ based on rs2032583 and rs2235015 were shown to according to this genetic test were reported to have affect antidepressant plasma concentration and symp- 69% more total health care visits, 67% more general tom improvement in a consistent way (Breitenstein medical visits, greater than 3-fold more medical et al. 2016). A more recent study investigated the clin- absence days, and greater than 4-fold more disability ical usefulness of FKBP5 rs1360780 genotyping and it claims (Winner et al. 2013a). Furthermore, the found that the risk allele showed a worse outcome in GeneSight test was reported to double the likelihood the treatment as usual arm compared to the geno- of response compared to treatment as usual in a typed-guided treatment arm (Stamm et al. 2016). Unfortunately, these studies investigating ABCB1 poly- small prospective randomised double-blind trial morphisms and FKBP5 rs1360780 clinical usefulness (Winner et al. 2013b) and similar findings were lack independent replication and did not provide any obtained in a larger open-label study (Hall-Flavin cost/benefit ratio estimation. et al. 2013). Finally, the GeneSight test was recently As reported above, a biomarker panel has been demonstrated to save $1,035.60 more in total medica- developed using serum-based testing to predict MDD. tion costs (both CNS and non-CNS medications) over

Results are interesting, but replication by independent 1 year compared to a non-tested standard care groups is also lacking. The test includes nine bio- cohort (Winner et al. 2015). In comparison, the com- markers (alpha1 antitrypsin, apolipoprotein CIII, BDNF, mercial pharmacogenetic Genecept Assay includes cortisol, epidermal growth factor, myeloperoxidase, polymorphisms in CYP2D6, CYP2C19, CYP3A4, SLC6A4, prolactin, resistin and soluble TNF-a receptor type II) HTR2C, DRD2, CACNA1C, ANK3, COMT, MTHFR, MC4R, and it demonstrated a sensitivity and specificity of 91.7 ADRA2A, BDNF, OPRM1 and GRIK1. This assay was and 81% in differentiating between MDD and healthy tested in a naturalistic study (Brennan et al. 2015) controls, respectively (Papakostas et al. 2013). Similar that did not include a comparison arm receiving findings were obtained in a further study by the same treatment as usual, thus statements regarding the authors, with an overall test accuracy of 91–94% clinical benefits of the test are particularly difficult. A depending on the sample (Bilello et al. 2015). No repli- study that did include patients treated as usual cation by independent investigators is available. reported higher medication adherence and cost savings in patients who underwent the test (Fagerness et al. 2014). Lastly, the CNSDose pharmacogenetic 7. Innovative biomarkers and methodological test includes polymorphisms in CYP2D6, CYP2C19, strategies UGT1A1, ABCB1 and ABCC1 genes and in a rando- New research perspectives recently emerged in terms mised trail patients receiving genotype-guided treat- of both biomarker type and methodological approach. ment showed a 2.52 greater probability of remission In particular, miRNAs were found to act as pivotal reg- (Singh 2015). Of note, replication by the same investi- ulators of mRNA degradation and thus mRNA transla- gators was found for the GeneSight test, but no inde- tion, providing complementary information to other pendent validation of any of the above reported biomarkers. miRNAs may also represent a relatively results was found. accessible method to therapeutically manipulate gene Two studies without commercial interest investi- expression, making them particularly interesting targets gated the clinical benefits of a genotype-guided treat- for future treatments. Indeed miRNAs can be detected ment versus treatment as usual. The first study in body fluids such as blood and they show unex- investigated the clinical usefulness of polymorphisms pected stability (Dwivedi 2016). For example, miR-16 18 C. FABBRI ET AL. was found to modulate SERT expression in different Genome-wide complex trait analysis is an alternative areas of the brain in response to antidepressants method that estimates the proportion of phenotypic (Baudry et al. 2010). In mice fluoxetine was demon- variance on the basis of the genetic relatedness strated to decrease the levels of miR-16 in the noradre- between individuals. Using this method, common var- nergic locus coeruleus and in the hippocampus, iants were estimated to explain 42% of individual dif- resulting in higher SERT expression in these areas, ferences in antidepressant response and 43% when increased BDNF secretion and hippocampal neurogen- considering only SSRIs (Tansey et al. 2013). In contrast, esis (Launay et al. 2011). In comparison, miR-135 has a polygenic score based on a meta-analysis of the been reported to modulate SERT as well as HTR1A GENDEP and MARS projects predicted only between expression and its levels are increased in mice after 0.5 and 1.2% of variance in improvement and remis- the administration of antidepressants (Issler et al. sion in the STAR*D sample (GENDEP, MARS, STAR*D 2014). Genetically modified mouse models, expressing Investigators, 2013), suggesting a significant but not higher or lower levels of miR-135, demonstrated major exciting overlap in terms of genetic variants involved alterations in anxiety- and depression-like behaviours, across different MDD samples. 5-HT levels, and behavioural response to antidepressant treatment. Finally, miR-135a levels in blood and 8. Conclusion brain of depressed human patients were demonstrated to be lower compared to controls (Issler et al. 2014). A Several biomarkers of MDD and antidepressant recent study including data on humans reported miR- response have been replicated at genetic, epigenetic 1202 as a promising marker of MDD and antidepres- and/or transcriptomic/proteomic levels (Table 1), des- sant response (Lopez et al. 2014). Interestingly, the tar- pite controversial findings often being reported. Genes gets of miR-1202 are genes involved in neurological consistently found in the replicated studies (e.g., processes associated with the pathogenesis of MDD, SLC6A4 and HTR2A) have been included in the first including the GRM4 gene that has been implicated in genetic tests investigated for clinical applicability the regulation of anxiety-related behaviours (Pilc et al. (Table 2). It is important to underline that a favourable 2008; Davis et al. 2012). Finally, a recent review cost/benefit ratio has not been clearly demonstrated

reported a comprehensive overview in regard to for any of the commercially available pharmacogenetic miRNA in MDD and antidepressant treatment (Dwivedi tests and currently no established clinical indications 2016). exist. The GeneSight test provided encouraging results, Under the methodological point of view, PRS are but the details regarding the algorithm used to classify worth note because they represent the most recent patients according to their genotype were not pub- attempt to capture the complexity of disease traits, lished. Therefore, replication of the results by inde- such as those found in MDD. PRS are obtained through pendent investigators has not been possible. The the sum of the effect sizes of SNPs with a certain level multi-assay, serum-based test that included nine bio- of association with a particular trait. Thus, they attempt markers for MDD diagnosis (Papakostas et al. 2013) to classify patients within a risk spectrum, or in other was performed on patients who already met the words to assign to each patient a risk of developing clinical DSM criteria for MDD, thus the cost/benefit bal- the trait in question (i.e. response to a drug or disease ance of this test is not clear. Furthermore, the predict- status). ive properties of the serum-based test have not been Previous studies using this approach found that a replicated by an independent group of investigators. genome-wide polygenic score was able to explain only MDD may be too heterogeneous to be useful for the small percentages of the variance in depression; for study of biomarkers. Given the broad nature of MDD, example, 1% was reported in elderly cohorts which most likely includes patients with many diverse (Demirkan et al. 2011; Musliner et al. 2015) and 0.2% aetiologies, it would be of interest to identify bio- when considering a long-term average depression marker panels to assist in identifying depression sub- score (Chang et al. 2014). Phenotypic and environmen- types, such as melancholia or psychotic depression. tal heterogeneity may explain these low percentages, Dimensional approaches to understand the risk and but the available evidence excluded that stressful life expression of mood disorders provide a different per- events may interact with PRS associated with depres- spective for the development of future diagnostic/ sion (Musliner et al. 2015). However, PRS were reported response-predictive tests. The Research Domain Criteria to have higher effect sizes as depressive symptom (Insel et al. 2010) focus on constructs under the nega- severity increased (Chang et al. 2014). Other possible tive valence systems domain (i.e., acute threat, poten- sources of heterogeneity were not investigated. tial threat, sustained threat, loss and frustrative non- THE WORLD JOURNAL OF BIOLOGICAL PSYCHIATRY 19 reward) and provide dimensional criteria that are Belzeaux R, Bergon A, Jeanjean V, Loriod B, Formisano- aimed at facilitating the identification of biomarkers of Treziny C, Verrier L, Loundou A, Baumstarck-Barrau K, biologically homogeneous alterations that exist across Boyer L, Gall V, et al. 2012. Responder and nonresponder patients exhibit different peripheral transcriptional signa- disorders. As we specified in the Introduction, it is not tures during major depressive episode. Transl Psychiatry. always easy to distinguish between markers of acute 2:e185. depressive phases (markers of state) and markers of Belzeaux R, Formisano-Treziny C, Loundou A, Boyer L, susceptibility to MDD, particularly for transcriptomic Gabert J, Samuelian JC, Feron F, Naudin J, Ibrahim EC. markers, and future studies investigating this issue are 2010. Clinical variations modulate patterns of gene expression and define blood biomarkers in major depression. warranted. Finally, the integration of different types of J Psychiatr Res. 44:1205–1213. biomarkers and the use of more complex multi-marker Belzeaux R, Loundou A, Azorin JM, Naudin J, Ibrahim el C. panels (that could be obtained through PRS, for 2014. Longitudinal monitoring of the serotonin transporter example) represent interesting strategies to pursue for gene expression to assess major depressive episode evolu- tion. Neuropsychobiology. 70:220–227. future clinical applications. 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